title: Structural plasticity in RNA and its role in the regulation of protein translation in coliphage Q beta.
abstract: We have analyzed both conformational and functional changes caused by two large cis-acting deletions (delta 159 and delta 549) located within the read-through domain, a 850 nucleotide hairpin, in coliphage Q beta genomic RNA. Studies in vivo show that co-translational regulation of the viral coat and replicase genes has been uncoupled in viral genomes carrying deletion delta 159. Translational regulation is restored in deletion delta 549, a naturally evolved pseudorevertant. Structural analysis by computer modeling shows that structural features within the read-through domain of delta 159 RNA are less well determined than they are in the read-through domain of wild-type RNA, whereas predicted structure in the read-through domain of evolved pseudorevertant delta 549 is unusually well determined. Structural analysis by electron microscopy of the genomic RNAs shows that several long range helices at the base of the read-through domain, that suppress translational initiation of the viral replicase gene in the wild-type genome, have been destabilized in delta 159 RNA. In addition, the structure of local hairpins within the read-through region is more variable in delta 159 RNA than in wild-type RNA. Stable RNA secondary structure is restored in the read-through domain of delta 549 RNA. Our analyses suggest that structure throughout the read-through domain affects the regulation of viral replicase expression by altering the likelihood that long-range interactions at the base of the domain will form. We discuss possible kinetic and equilibrium models that can explain this effect, and argue that observed changes in structural plasticity within the read-through domain of the mutant genomes are key in understanding the process. During the course of these studies, we became aware of the importance of the information contained in the energy dot plot produced by the RNA secondary structure prediction program mfold. As a result, we have improved the graphical representation of this information through the use of color annotation in the predicted optimal folding. The method is presented here for the first time.
authors.affiliation: Department of Microbiology, State University of New York, Stony Brook 11794-5222, USA.
authors.forename: A B
authors.initials: AB
authors.lastname: Jacobson
authors.forename: R
authors.initials: R
authors.lastname: Arora
authors.forename: M
authors.initials: M
authors.lastname: Zuker
authors.forename: C
authors.initials: C
authors.lastname: Priano
authors.forename: C H
authors.initials: CH
authors.lastname: Lin
authors.forename: D R
authors.initials: DR
authors.lastname: Mills
mesh_terms: D017908:Allolevivirus / Q000737:chemistry / Q000235:genetics* / Q000648:ultrastructure; D002213:Capsid / Q000235:genetics; D003198:Computer Simulation; D016679:Genome, Viral; D008854:Microscopy, Electron; D008958:Models, Molecular; D009690:Nucleic Acid Conformation; D014176:Protein Biosynthesis; D012367:RNA, Viral / Q000737:chemistry* / Q000502:physiology* / Q000648:ultrastructure
chemical_list: D012367:RNA, Viral